feat: Introduce .env configuration file and remove legacy .env_example; enhance intelligent routing service for better error handling and CSV analysis

Author: samadpls

.env_examp

@@ -0,0 +1,9 @@
+GROQ_API_KEY=your_groq_api_key_here
+GROQ_MODEL_NAME=model/name
+
+APP_NAME=Querypls
+APP_VERSION=1.0.0
+MAX_TOKENS=1000
+TEMPERATURE=0.7
+MAX_CHAT_HISTORIES=5
+LOG_LEVEL=INFO

.env_example

@@ -7,24 +7,31 @@
 [![License](https://img.shields.io/badge/License-MIT%202.0-blue.svg)](LICENSE)
 <img src='https://img.shields.io/github/stars/samadpls/querypls?color=red&label=stars&logoColor=black&style=social'>
 
-# 💬 Querypls - Prompt to SQL 
+# 💬 Querypls - Intelligent SQL and CSV Analysis
 
-Querypls is a web application that provides an interactive chat interface, simplifying SQL query generation. Users can effortlessly enter SQL queries and receive corresponding results. The application harnesses the capabilities of the language models from Hugging Face to generate SQL queries based on user input.
+Querypls is a modern web application that provides an interactive chat interface for SQL query generation and CSV data analysis. Built with Pydantic AI and powered by OpenAI's GPT-OSS-120B model through Groq, it offers intelligent routing between different analysis modes to handle various data-related queries.
+
+🌐 **Try it live**: [querypls.streamlit.app](https://querypls.streamlit.app/)
 
 ## Key Features
 
-💬 Interactive chat interface for easy communication.  
-🔍 Enter SQL queries and receive query results as responses.  
-🤖 Utilizes language models from Hugging Face for advanced query generation ([Querypls-prompt2sql](https://huggingface.co/samadpls/querypls-prompt2sql)).  
-💻 User-friendly interface for seamless interaction.  
+💬 **Interactive Chat Interface** - Natural language conversations for data analysis  
+🔍 **SQL Query Generation** - Convert natural language to optimized SQL queries  
+📊 **CSV Data Analysis** - Upload and analyze CSV files with intelligent insights  
+🤖 **Intelligent Routing** - Automatically determines the best agent for your query  
+⚡ **Fast Inference** - Powered by Groq's optimized infrastructure  
+🔒 **Type-Safe Development** - Built with Pydantic AI for robust validation  
+📈 **Visual Analytics** - Generate charts and visualizations from your data  
 
 ![QueryplsDemo](https://github.com/samadpls/Querypls/assets/94792103/daa6e37d-a256-4fd8-9607-6e18cf41df3f)
 
 
 
 # Acknowledgments
 
-`Querypls` received a shoutout from [🦜 🔗 Langchain](https://www.langchain.com/) on their Twitter, reaching over **60,000 impressions**. Additionally, it was featured under the **Community Favorite Projects** section on `🦜 🔗 Langchain's blog`, leading to a significant increase in stars for this repository and a growing user base. The project was also highlighted in a [YouTube video](https://www.youtube.com/watch?v=htHVb-fK9xU), and it also caught the attention of Backdrop, expressing their interest and liking in an email, inviting the project to be a part of their hackathon.
+`Querypls` received a shoutout from [🦜 🔗 Langchain](https://www.langchain.com/) on their Twitter in 2023, reaching over **60,000 impressions**. Additionally, it was featured under the **Community Favorite Projects** section on `🦜 🔗 Langchain's blog`, leading to a significant increase in stars for this repository and a growing user base. The project was also highlighted in a [YouTube video](https://www.youtube.com/watch?v=htHVb-fK9xU), and it also caught the attention of Backdrop, expressing their interest and liking in an email, inviting the project to be a part of their hackathon.
+
+However, due to constant breakdowns and instability issues with the LangChain framework, we made the strategic decision to migrate to **Pydantic AI** - a more stable and reliable framework. This transition has brought improved performance, better type safety, and enhanced maintainability to the project.
 
 | [🔗 Langhchain Twitter Post](https://twitter.com/LangChainAI/status/1729959981523378297?t=Zdpw9ZQYvE3QS-3Bf-xaGw&s=19) | [🔗 Langhcain Blog Post](https://blog.langchain.dev/week-of-11-27-langchain-release-notes/) | 
 |----------|----------|
@@ -38,7 +45,7 @@ This project is licensed under the MIT License. See the [LICENSE](LICENSE) file
 
 
 > [!Note]  
-> Querypls, while powered by a 7B model of Satablility AI LLM Model, is currently limited in providing optimal responses for simple queries.
+> Querypls is now powered by OpenAI's GPT-OSS-120B model through Groq, providing fast and reliable AI-powered SQL generation and CSV analysis capabilities.
 
 ---
 
@@ -59,11 +66,11 @@ This project is licensed under the MIT License. See the [LICENSE](LICENSE) file
     pip install -r requirements.txt
     ```
 
-4. Create a `.env` file based on `.env_example` and set the necessary variables.
+4. Create a `.env` file based on `.env_examp` and set the necessary variables.
 
 5. Run the application:
     ```bash
-    streamlit run src/app.py
+    streamlit run src/frontend/app.py
     ```
 
 6. Open the provided link in your browser to use Querypls.

README.md

@@ -17,19 +17,15 @@ class Settings(BaseModel):
     debug_mode: bool = Field(default=False, env="DEBUG_MODE")
 
     # Legacy fields for backward compatibility
-    app_name: Optional[str] = Field(None, env="APP_NAME")
-    streamlit_port: Optional[str] = Field(None, env="STREAMLIT_PORT")
-    streamlit_host: Optional[str] = Field(None, env="STREAMLIT_HOST")
-    max_tokens: Optional[str] = Field(None, env="MAX_TOKENS")
-    temperature: Optional[str] = Field(None, env="TEMPERATURE")
-    log_level: Optional[str] = Field(None, env="LOG_LEVEL")
+    max_tokens: Optional[str] = Field(1000, env="MAX_TOKENS")
+    temperature: Optional[str] = Field(0.7, env="TEMPERATURE")
+    log_level: Optional[str] = Field("INFO", env="LOG_LEVEL")
 
     json_schema_extra: ClassVar[str] = "ignore"
 
     model_config = ConfigDict(
         env_file = ".env",
         env_file_encoding = "utf-8",
-        # Add any necessary configuration here
     )